File size: 2,570 Bytes
718be7e 1d15b75 718be7e 1d15b75 718be7e 26b6c38 718be7e 1d15b75 718be7e 1d15b75 718be7e |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 |
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: hubert-large-ls960-ft-finetuned-gtzan
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# hubert-large-ls960-ft-finetuned-gtzan
This model is a fine-tuned version of [facebook/hubert-large-ls960-ft](https://huggingface.co/facebook/hubert-large-ls960-ft) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7096
- Accuracy: 0.85
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 8e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 18
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.2623 | 1.0 | 56 | 2.2399 | 0.21 |
| 1.881 | 1.99 | 112 | 1.7105 | 0.41 |
| 1.5793 | 2.99 | 168 | 1.6203 | 0.46 |
| 1.3018 | 4.0 | 225 | 1.3824 | 0.52 |
| 1.0219 | 5.0 | 281 | 0.9899 | 0.66 |
| 0.9047 | 5.99 | 337 | 0.8812 | 0.74 |
| 0.8353 | 6.99 | 393 | 0.7629 | 0.78 |
| 0.659 | 8.0 | 450 | 0.9674 | 0.71 |
| 0.645 | 9.0 | 506 | 0.8953 | 0.74 |
| 0.6233 | 9.99 | 562 | 0.6638 | 0.8 |
| 0.4155 | 10.99 | 618 | 0.6323 | 0.81 |
| 0.2689 | 12.0 | 675 | 0.5423 | 0.83 |
| 0.3714 | 13.0 | 731 | 0.6770 | 0.83 |
| 0.0692 | 13.99 | 787 | 0.6260 | 0.83 |
| 0.0778 | 14.99 | 843 | 0.5801 | 0.85 |
| 0.187 | 16.0 | 900 | 0.6722 | 0.83 |
| 0.1469 | 17.0 | 956 | 0.7473 | 0.85 |
| 0.1052 | 17.92 | 1008 | 0.7096 | 0.85 |
### Framework versions
- Transformers 4.30.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3
|